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Engineering hierarchical quaternary superstructure of an integrated MOF-derived electrode for boosting urea electrooxidation assisted water electrolysis

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Green Energy & Environment 2024年第4期9卷 695-701页

作者： Jianjun Tian Changsheng Cao Yingchun He muhammad imran khan Xin-Tao Wu Qi-Long Zhu State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of MatterChinese Academy of Sciences(CAS)Fuzhou350002China Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou350108China University of Chinese Academy of Sciences Beijing100049China Research Institute of Sciences and Engineering(RISE) University of SharjahSharjah27272United Arab Emirates

Controllable design of the catalytic electrodes with hierarchical superstructures is expected to improve their electrochemical performance.Herein,a self-supported integrated electrode(NiCo-ZLDH/NF)with a unique hierarchical quaternary superstructure was fabricated through a self-sacrificing template strategy from the metal–organic framework(Co-ZIF-67)nanoplate arrays,which features an intriguing well-defined hierarchy when taking the unit cells of the NiCo-based layered double hydroxide(NiCo-LDH)as the primary structure,the ultrathin LDH nanoneedles as the secondary structure,the mesoscale hollow plates of the LDH nanoneedle arrays as the tertiary structure,and the macroscale three-dimensional frames of the plate arrays as the quaternary structure.Notably,the distinctive structure of NiCo-ZLDH/NF can not only accelerate both mass and charge transfer,but also expose plentiful accessible active sites with high intrinsic activity,endowing it with an excellent electrochemical performance for urea oxidation reaction(UOR).Specially,it only required the low potentials of 1.335,1.368 and 1.388 V to deliver the current densities of 10,100 and 200 mA cm^(-2),respectively,much superior to those for typical NiCo-LDH.Employing NiCo-ZLDH/NF as the bifunctional electrode for both anodic UOR and cathodic HER,an energy-saving electrolysis system was further explored which can greatly reduce the needed voltage of 213 mV to deliver the current density of 100 mA cm^(-2),as compared to the conventional water electrolysis system composed of OER.This work manifests that it is prospective to explore the hierarchically nanostructured electrodes and the innovative electrolytic technologies for high-efficiency electrocatalysis.

关键词： Hierarchical superstructures Metal–organic frameworks Layered double hydroxides Urea oxidation reaction Hydrogen evolution reaction

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Modelling of debris-flow susceptibility and propagation: a case study from Northwest Himalaya

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Journal of Mountain Science 2024年第1期21卷 200-217页

作者： Hamza DAUD Javed Iqbal TANOLI Sardar muhammad ASIF muhammad QASIM muhammad ALI Junaid khan Zahid imran BHATTI Ishtiaq Ahmad khan JADOON Badong National Observation and Research Station of Geohazards China University of GeosciencesWuhan 430074China Department of Earth Sciences COMSATS University IslamabadAbbottabad Campus 22010Pakistan Department of Earth Sciences Sultan Qaboos UniversityAl-KhoudMascat 123Oman Faculty of Engineering China University of Geosciences(Wuhan)Wuhan 430074China Department of Earth Sciences Abbottabad University of Science and TechnologyHavelian 22500Pakistan

The geological and geographical position of the Northwest Himalayas makes it a vulnerable area for mass movements particularly landslides and debris flows. Mass movements have had a substantial impact on the study area which is extending along Karakorum Highway(KKH) from Besham to Chilas. Intense seismicity, deep gorges, steep terrain and extreme climatic events trigger multiple mountain hazards along the KKH, among which debris flow is recognized as the most destructive geohazard. This study aims to prepare a field-based debris flow inventory map at a regional scale along a 200 km stretch from Besham to Chilas. A total of 117 debris flows were identified in the field, and subsequently, a point-based debris-flow inventory and catchment delineation were performed through Arc GIS analysis. Regional scale debris flow susceptibility and propagation maps were prepared using Weighted Overlay Method(WOM) and Flow-R technique sequentially. Predisposing factors include slope, slope aspect, elevation, Topographic Roughness Index(TRI), Topographic Wetness Index(TWI), stream buffer, distance to faults, lithology rainfall, curvature, and collapsed material layer. The dataset was randomly divided into training data(75%) and validation data(25%). Results were validated through the Receiver Operator Characteristics(ROC) curve. Results show that Area Under the Curve(AUC) using WOM model is 79.2%. Flow-R propagation of debris flow shows that the 13.15%, 22.94%, and 63.91% areas are very high, high, and low susceptible to debris flow respectively. The propagation predicated by Flow-R validates the naturally occurring debris flow propagation as observed in the field surveys. The output of this research will provide valuable input to the decision makers for the site selection, designing of the prevention system, and for the protection of current infrastructure.

关键词： North Pakistan Debris flow Flow-R Propagation Susceptibility mapping Debris-flow inventory Weighted Overlay Method

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Enhanced Steganalysis for Color Images Using Curvelet Features and Support Vector Machine

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Computers, Materials & Continua 2024年第1期78卷 1311-1328页

作者： Arslan Akram imran khan Javed Rashid Mubbashar Saddique muhammad Idrees Yazeed Yasin Ghadi Abdulmohsen Algarni Faculty of Computer Science and Information Technology Department of Computer ScienceSuperior UniversityLahore54000Pakistan Machine Learning Code(MLC)Lab Meharban HouseHouse Number 209Zafar ColonyOkara56300Pakistan Information Technology Services University of OkaraOkara56310Pakistan Department of Computer Science&Engineering University of Engineering&Technology LahoreNarowal CampusNarowal51601Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain11671Abu Dhabi Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Algorithms for steganography are methods of hiding data transfers in media files.Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information,and these methods have made it feasible to handle a wide range of problems associated with image analysis.Images with little information or low payload are used by information embedding methods,but the goal of all contemporary research is to employ high-payload images for classification.To address the need for both low-and high-payload images,this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to efficiently extract characteristics from both type of images.Support Vector Machine(SVM),a commonplace classification technique,has been employed to determine whether the image is a stego or cover.The Wavelet Obtained Weights(WOW),Spatial Universal Wavelet Relative Distortion(S-UNIWARD),Highly Undetectable Steganography(HUGO),and Minimizing the Power of Optimal Detector(MiPOD)steganography techniques are used in a variety of experimental scenarios to evaluate the performance of the proposedmethod.Using WOW at several payloads,the proposed approach proves its classification accuracy of 98.60%.It exhibits its superiority over SOTA methods.

关键词： Curvelets fast fourier transformation support vector machine high pass filters steganography

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Depositional and Bio-Sequence Stratigraphic Framework of Late Cretaceous Kawagarh Formation,Kala-Chitta Range,Pakistan:Equivalent of Gurpi Formation(Iran)

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Journal of Earth Science 2024年第2期35卷 332-348页

作者： muhammad Awais Bilal Wadood muhammad Ishaq muhammad Bilal Zeeshan Zafar Nasar khan Aminullah khan Department of Geology University of SwabiAnbar-SwabiKhyber PakhtunkhwaSwabi23561Pakistan Department of Earth Environmental and Resources SciencesUniversity of Naples FedericoⅡNaples80126Italy State Key Laboratory of Continental Dynamics Department of GeologyNorthwest UniversityXi’an710069China National Centre of Excellence in Geology University of PeshawarPeshawarKhyber Pakhtunkhwa25130Pakistan Department of Geological Engineering School of Earth Sciences and EngineeringXi’an Shiyou UniversityXi’an610500China Department of Petroleum Geology and Engineering School of Earth ResourcesChina University of GeosciencesWuhan430074China Department of Geology University of MalakandDir Lower18800ChakdaraPakistan Department of Earth and Environmental Sciences KU LeuvenLeuven3001Belgium

The present study is focused on evaluation of deep marine pelagic sediments of Late Cretaceous Kawagarh Formation of Kala-Chitta Range in the context of microfacies analysis,paleoenvironmental interpretation,planktonic foraminiferal biostratigraphy,sequence stratigraphy and diversification of species.A total of thirty three rock samples were collected from the measured section.Three microfacies are interpreted,namely planktonic foraminifera wackestone,planktonic foraminifera mudstone and sandy mudstone indicating low energy depositional environment i.e.,outer ramp.The biostratigraphic studies show plentiful planktonic foraminifera species of Globotruncana,Heterohelix and Globotruncanita.However,no association of benthic or siliceous organisms was observed.On the basis of available species assemblage,a single local planktonic foraminifera biozone i.e.,Globotruncana-Heterohelix-Globotruncanita Assemblage Biozone is established.The biozone information is combined with published literature and Lower Santonian to Middle Maastrichtian age has been assigned to the Kawagarh Formation.The trend of species occurrences evinces that species number decreases over time with pulsated rise in the Kawagarh Formation.The Kawagarh Formation carbonates show an overall Transgressive Systems Tract(TST).The Kawagarh Formation of Pakistan evinces analogous characteristics to that of the Late Cretaceous Gurpi Formation of Iran based on the geologic age,outcrop lithology,microfacies,planktonic foraminiferal assemblages,depositional setting and sequence stratigraphy.

关键词： depositional fabric biostratigraphy sequence stratigraphy Late Cretaceous Kawagarh Formation Pakistan Gurpi Formation Iran

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A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

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Computers, Materials & Continua 2024年第3期78卷 2967-3000页

作者： Usman khan muhammad Khalid khan muhammad Ayub Latif muhammad Naveed muhammad Mansoor Alam Salman A.khan Mazliham Mohd Su’ud College of Computing and Information Sciences Karachi Institute of Economics and TechnologyKarachi75190Pakistan Faculty of Computing and Informatics(FCI) Multimedia UniversityCyberjaya63100Malaysia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyAustralia

Recently,there has been a notable surge of interest in scientific research regarding spectral images.The potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable attention.One encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image classification.As a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent beneficiaries.This paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and vegetables.By meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical use.Additionally,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural context.The findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in agriculture.Nevertheless,we also shed light on the various issues and limitations of working with spectral images.This comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

关键词： Machine learning deep learning unmanned aerial vehicles multi-spectral images image recognition object detection hyperspectral images aerial photography

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Experimental Study on Heat Storage Properties Comparison of Paraffin/Metal Foams Phase Change Material Composites

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Journal of Thermal Science 2024年第2期33卷 469-478页

作者： Waqar AHMED Abid HUSSAIN Hanzla SHAHID imran ALI Hafiz muhammad ALI Department of Mechanical Engineering University of Engineering and TechnologyTaxila47080Pakistan Department of Mechanical Engineering Institute of Space TechnologyIslamabadPakistan Department of Mechanical Mechatronics and Manufacturing EngineeringUniversity of Engineering and Technology LahoreFaisalabad CampusPunjabPakistan Mechanical Engineering Department King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

Heat storage properties of phase change materials(PCMs) are essential characteristics that perform a key role in thermal heat energy storage systems.The thermal properties of PCMs can be improved by developing metal foam/PCM composites.The addition of metal foam in PCMs has a significant effect on the thermal characteristics of PCMs.In this paper,the heat storage properties of two different metal foam/PCM composites were experimentally examined.The behavior of paraffin in metal foam(copper and iron-nickel)/paraffin composites concerning pure paraffin at a constant heat flux of 1000 W/m^(2) in three directions simultaneously(x,y,and z) was studied.Paraffin was infiltrated into copper and iron-nickel foams to develop composite materials which resulted in enhancing the thermal conductivity of the paraffin.A comparative analysis is made on the heat storage properties of paraffin in copper and iron-nickel foams/paraffin composites.Inner temperature distribution during the phase transition process is experimentally evaluated.This comparison indicates that temperature uniformity in copper foam/paraffin composite is better than in iron-nickel foam/paraffin composite and pure paraffin at the same heat flux.Experimental results show that at heat flux of 1000 W/m^(2),the heat storage time for copper foam/paraffin composite is 20.63% of that of iron-nickel foam/paraffin composite.

关键词： heat storage capacity paraffin/metal foam composite temperature uniformity heat storage rate phase transition process

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Unraveling the role of NiSnPH@OOH/CC perovskite hydroxide for efficient electrocatalytic oxidation of methanol to formate

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Nano Research 2024年第4期17卷 2388-2399页

作者： Jing Shao Yusheng Fang Xiaobing Wu muhammad imran Abdullah Youkun Tao College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China School of Science Harbin Institute of TechnologyShenzhen 518055China

The sluggish kinetics of oxygen evolution reaction(OER)is the key tailback for hydrogen production from the water electrolysis.Masking OER with thermodynamically auspicious methanol oxidation reaction(MOR)can significantly boost the H_(2) and value-added products production.However,it is currently challenging to achieve a synergistic manipulation of product selectivity and performance for MOR electrocatalyst.Herein,we report NiSnPH@OOH/CC(CC=carbon cloth)perovskite hydroxide nanosphere as an efficient MOR electrocatalyst with high activity,stability,and selectivity towards methanol oxidation to formate.A surface amorphous layer of defect rich NiOOH was generated in operando by selective Sn leaching with stable perovskite hydroxide bulk structure,which mitigates the oxidative power and optimizes the local coordination environment of the active NiOOH sites.In situ Raman combined with electrochemical studies further confirm the key active species,NiOOH,generated in operando enhance the MOR and blocking the over oxidation of methanol to CO_(2).As a result,NiSnPH@OOH/CC effectively masks the OER and attains>99%selectivity with 100%Faradic efficiency for methanol-to-formate.The results of this study show the advances of NiSnPH@OOH/CC as an efficient electrocatalyst for MOR and also suggest its potential applications for various small organic molecules oxidation.

关键词： perovskite hydroxide small organic molecules nickel oxy(hydroxide) value-added products methanol oxidation reaction

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Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy muhammad Adnan khan muhammad Hasnain Azam khan muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or pathologic.Various cardiotocography measures infer wrongly and give wrong predictions because of human error.The traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as well.Fetal condition is very important to measure at numerous stages and give proper medications to the fetus for its well-being.In the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional results.ML techniques play a pivotal role in detecting fetal disease in its early stages.This research article uses Federated machine learning(FML)and ML techniques to classify the condition of the fetus.This study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the data.So,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,respectively.So,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

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Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

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Computers, Materials & Continua 2024年第5期79卷 3333-3353页

作者： Aiman muhammad Arshad Bilal khan Sadique Ahmad muhammad Asim Department of Computer Science City University of Science and Information TechnologyPeshawar25000Pakistan EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia School of Computer Science and Technology Guangdong University of TechnologyGuangzhou510006China

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,etc.However, the research on RomanUrdu is not up to the mark.Hence, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

关键词： Digital forensics author profiling for security AdaBoostM1 random forest ensemble learning

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Insight into the dynamics of non-Newtonian Carreau fluid when viscous dissipation,entropy generation,convective heating and diffusion are significant

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Applied Mathematics(A Journal of Chinese Universities) 2024年第1期39卷 34-46页

作者： ZHOU Shuang-shuang muhammad Ijaz khan Sami Ullah khan Sumaira Qayyum School of Science Hunan City UniversityYiyang 413000China Department of Mechanical Engineering Prince Mohammad Bin Fahd UniversityP.O.Box1664Al-Khobar 31952Kingdom of Saudi Arabia Department of Mathematics Namal UniversityMianwali 42250Pakistan Department of Mathematics Quaid-I-Azam University 45320Islamabad 44000Pakistan

The investigation endorsed the convective flow of Carreau nanofluid over a stretched surface in presence of entropy generation optimization.The novel dynamic of viscous dissipation is utilized to analyze the thermal mechanism of magnetized flow.The convective boundary assumptions are directed in order to examine the heat and mass transportation of nanofluid.The thermal concept of thermophoresis and Brownian movements has been re-called with the help of Buongiorno model.The problem formulated in dimensionless form is solved by NDSolve MATHEMATICA.The graphical analysis for parameters governed by the problem is performed with physical applications.The affiliation of entropy generation and Bejan number for different parameters is inspected in detail.The numerical data for illustrating skin friction,heat and mass transfer rate is also reported.The motion of the fluid is highest for the viscosity ratio parameter.The temperature of the fluid rises via thermal Biot number.Entropy generation rises for greater Brinkman number and diffusion parameter.

关键词： heat generation surface reaction CNTs based nano uid stretching/shrinking sheet thermal radiation

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